Digital halftoning refers to any algorithmic process which creates the illusion of continuous-tone images from the judicious arrangement of binary picture elements (pixels).
RIPing (Raster Image Processing) is the digital image processing that takes a continuous-tone image and original graphical elements and provides a binary halftoned output image file. RIPing an image file usually can include the steps of spatial filtering, interpolation, tone and color modification, and digital halftoning
There is a need to control the size of the dots in a pre-existing halftone bitmap. This bitmap could have been generated by a digital screening system (i.e., a RIP) or it could have been generated by scanning an optical piece of film to create a digital bitmap file. In general, these bitmap files were created with some output device in mind. As such, the dot pattern was created to produce a given density to dot percentage relationship tailored to the target output device. If this bitmap file were printed on an output device that had different dot-gain characteristics than the target device the density as a function of dot-area percentage will be different Thus, in order to achieve the desired dot percentage to output density relationship of the target device, on a different device, the bitmap file for the target device must be modified according to the dot-gain differences between the target device and the given output device.
For most traditional digital-proofing scenarios this dot-gain compensation is done by re-RIPing the original art with a modified dot-gain curve. This modified dot-gain curve accounts for the dot-gain differences between the target device and the proofing system. Thus, a custom bitmap file needs to be generated for each output device. The main drawback to this paradigm is that the proofs may be made on systems that do not use the same screening technology as was used to create the target bitmap file. Thus, in order to support a RIP-once-output-many (ROOM) workflow the dot-gain compensation needs to be applied to the bitmap file directly
The present invention offers an efficient technique to adjust the dot sizes of bitmap image files such that the color and tone of the bitmap files can be adjusted prior to printing. These bitmap files can consist of single channel bitmaps such as those for a single color device (e g, a black-and-white laser printer), those for a CMYK output device (e g., a printing press or a graphic-arts proofer), or any output device that utilizes bitmap files of any number of channels (e g, a multi-ink inkjet printer). In the present invention the color and tone of the bitmap files are adjusted by growing or shrinking the size of the bitmap dots using an erosion/dilation based halftone dot-growth technique using a dot edge-detection scheme.
In short, this technique identifies the edges of the halftone dots and either selectively adds or removes binary pixels (bitmap dots) to or from these edges to control the size of the halftone dots. The edges of the halftone dots are obtained using the morphological image processing technique of boundary detection using dilation and erosion depending on whether the dot in question needs to increase in size or decrease in size respectively. The exterior boundary of a dot feature is detected using a dilation based boundary detection process. The interior boundary of a dot feature is detected using an erosion based boundary detection process. The structuring elements used in the edge detection process can be tailored depending on the dot-growth task. The amount that a given dot percentage needs to grow or shrink is defined by a dot-gain curve.
Several approaches for dot-gain modification of bitmaps have been proposed. The dot gain may be adjusted for each of the primary colors cyan, magenta, yellow, and black. A description for how to do this is disclosed by Spence in U.S. Pat. Nos. 5,255,085 and 5,293,539 titled “ADAPTIVE TECHNIQUE FOR PROVIDING ACCURATE TONE REPRODUCTION CONTROL IN AN IMAGING SYSTEM” and “METHOD AND APPARATUS FOR CALIBRATING TONE REPRODUCTION IN A PROOFING SYSTEM”. Here, percent dot area is calculated using the Murray and Davies equation from measured densities.
Denber, et. al disclose a method of shifting and ANDING a bitmap image with itself to thin the image displayed in U.S. Pat. No. 5,250,934 “METHOD AND APPARATUS FOR THINNING PRINTED IMAGES” and also teaches a method of setting a bit to an intermediate level if it is diagonally between two active bits using shifting, logical AND, and a logical OR operation.
Mailloux, et al discloses using a 4×4 input to a lookup table to determine how to operate on the central 2×2 pixels to implement halfbit or fullbit dilation and erosion in U.S. Pat. No. 5,483,351 titled “DILATION OF IMAGES WITHOUT RESOLUTION CONVERSION TO COMPENSATE FOR PRINTER CHARACTERISTICS”. This requires knowing some of the surrounding pixels when deciding how to dilate or erode the pixels in the center.
Eschbach teaches in U.S. Pat. No. 5,258,854 titled “CONVERTING BETWEEN WRITE-WHITE, WRITE-BLACK, AND NEUTRAL BITMAPS”, how to resize bitmap images in small amounts less than one full bit in size. Eschbach states that the erosion and dilation may be by differing amounts in the x and y directions, and that the amount of resizing may be a fraction of a full pixel.
Loce, et al teaches logically combining two morphological filter pairs and an original image to create an output image in U.S. Pat. No. 5,680,485 titled “METHOD AND APPARATUS EMPLOYING EROSION-BASED FILTER PAIRS FOR IMAGE MAPPING”. The morphological filters described are erosion filters, one of which has less erosion than desired and the other having more erosion than desired Logically combining combinations of the original image with the two eroded images provides for a method of obtaining an intermediate result.
Eschbach describes a method of resizing an input bitmap in U.S. Pat. No. 5,208,871 titled “PIXEL QUANTIZATION WITH ADAPTIVE ERROR DIFFUSION” Eschbach simulates a scan of an output image from an input bitmap such that the scan resolution is different from the input bitmap. Error diffusion is utilized to quantize the output bitmap into the desired output bit resolution This example uses en-or diffusion to spread out the error in the quantization of a multilevel pixel into a reduced number of output states.
None of the afore mentioned patents address the issues associated with adjusting the halftone bitmap image dot shape up and down the tone scale. U.S. Pat. No. 6,115,140, inventors Bresler and Nosko, issued Sep. 5, 2000, is of interest. This patent teaches a method for color correcting a halftone bitmap image using a dilation and erosion based filtering process which generates a set of filtered halftone bitmap images that can be merged together to create a color corrected halftone bitmap image. The process has several limitations that limit its quality and usefulness In their process, Bresler and Nosko take an original halftone bitmap image and perform the morphological filtering process of dilation and erosion to create a series of filtered halftone bitmaps images. In their process, they teach a method where their dilation process adds a complete layer of on pixels around the original halftone dot features present in the halftone bitmap image. This process is illustrated in FIG. 9 of this patent application. Notice that in FIG. 9 three levels of dilation of the original feature are shown. Also referring to FIG. 9 the original bitmap (700) is dilated to produce a once-dilated bitmap (702). Subsequent dilation of the once-dilated bitmap (702) produces a twice-dilated bitmap (704). Subsequent dilation of the twice-dilated bitmap (704) produces a three-times dilated bitmap (706)
Their output halftone bitmap image consists of a dithered (or weighted) combination of the dilated or eroded halftone bitmap images. The dithering operation is controlled by continuous-tone estimates of the halftone bitmap images generated using a descreening process. This dithering operation can take on the form of simple fixed threshold or more complicated variable threshold techniques. Inherently, this process suffers from rounding errors that can produce unwanted texture into the resulting bitmap.